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Artificial intelligence (AI) and interventional radiotherapy (brachytherapy): state of art and future perspectives
by
Tagliaferri, Luca
, Lancellotta, Valentina
, Patarnello, Stefano
, Boldrini, Luca
, Gambacorta, Maria
, Fionda, Bruno
, D’Aviero, Andrea
, Kovács, György
, Valentini, Vincenzo
in
artificial intelligence
/ brachytherapy
/ decision supporting system
/ interventional radiotherapy
/ machine learning
/ personalized medicine
/ Review Paper
2020
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Artificial intelligence (AI) and interventional radiotherapy (brachytherapy): state of art and future perspectives
by
Tagliaferri, Luca
, Lancellotta, Valentina
, Patarnello, Stefano
, Boldrini, Luca
, Gambacorta, Maria
, Fionda, Bruno
, D’Aviero, Andrea
, Kovács, György
, Valentini, Vincenzo
in
artificial intelligence
/ brachytherapy
/ decision supporting system
/ interventional radiotherapy
/ machine learning
/ personalized medicine
/ Review Paper
2020
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Do you wish to request the book?
Artificial intelligence (AI) and interventional radiotherapy (brachytherapy): state of art and future perspectives
by
Tagliaferri, Luca
, Lancellotta, Valentina
, Patarnello, Stefano
, Boldrini, Luca
, Gambacorta, Maria
, Fionda, Bruno
, D’Aviero, Andrea
, Kovács, György
, Valentini, Vincenzo
in
artificial intelligence
/ brachytherapy
/ decision supporting system
/ interventional radiotherapy
/ machine learning
/ personalized medicine
/ Review Paper
2020
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Artificial intelligence (AI) and interventional radiotherapy (brachytherapy): state of art and future perspectives
Journal Article
Artificial intelligence (AI) and interventional radiotherapy (brachytherapy): state of art and future perspectives
2020
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Overview
Artificial intelligence (AI) plays a central role in building decision supporting systems (DSS), and its application in healthcare is rapidly increasing. The aim of this study was to define the role of AI in healthcare, with main focus on radiation oncology (RO) and interventional radiotherapy (IRT, brachytherapy).
AI in RO has a large impact in providing clinical decision support, data mining and advanced imaging analysis, automating repetitive tasks, optimizing time, and modelling patients and physicians' behaviors in heterogeneous contexts. Implementing AI and automation in RO and IRT can successfully facilitate all the steps of treatment workflow, such as patient consultation, target volume delineation, treatment planning, and treatment delivery.
AI may contribute to improve clinical outcomes through the application of predictive models and DSS optimization. This approach could lead to reducing time-consuming repetitive tasks, healthcare costs, and improving treatment quality assurance and patient's assistance in IRT.
Publisher
Termedia Publishing House
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